Back to Shadi AI PRODUCT FACULTY
Project documentation

Shadi AI.

By Varun Maryada

Shadi AI is an AI-powered wedding planning platform designed for the Indian diaspora in North America.

The problem

Indian diaspora weddings involve 4–6 events, 20–30+ vendors, 300–400+ guests, and $225K–$285K in spend over 12–18 months — but every major planning platform was architected around a single-day Western wedding. Planners and couples run Indian wedding complexity inside tools that were never built for it, patching together Aisle Planner, Google Sheets, and WhatsApp.

Within that, contract review is a standout pain: planners and couples sign 20–30 vendor contracts per wedding with no tool to help them understand what they're agreeing to, and one missed clause destroys trust permanently. It's a 45-minute manual task per contract with no cultural or industry benchmark.

The solution

Shaadi AI is a wedding planning platform built natively for North American Indian diaspora weddings, and its flagship capability is the AI Contract Intelligence Suite — complete white space with no competitor equivalent.

From a single contract upload, it returns a plain-language summary, traffic-light flags (green/yellow/red) benchmarked against Indian wedding market norms, a one-click negotiation email, and an obligation tracker. Rather than using AI only for aesthetic inspiration, Shaadi AI uses it to eliminate manual work — turning a 45-minute contract review into roughly 5 minutes, and building the trust that unlocks the platform's other AI features across budgeting, outreach, and guest management.

How it works

The contract flow moves from upload (PDF or pasted text, with vendor name and category) through a visible three-stage pipeline — extracting text, analyzing clauses, generating summary — to four outputs: a plain-language summary at an 8th-grade reading level with an overall LOW/MEDIUM/HIGH risk banner; per-clause traffic-light flags with a one-sentence industry-norm benchmark; one-click response drafting in the planner's tone; and, on marking the contract signed, automatic extraction of payment deadlines and obligations into a tracker.

A core system prompt casts the assistant as culturally fluent in Indian wedding structure, applying domain knowledge — such as that cancellation clauses in these contracts frequently lack standard force majeure protections — without being asked. Industry-norm benchmarking is built into the prompt initially and improves as real contract data accumulates.

Who it's for

Shaadi AI serves two primary users. The highest-revenue user is the Indian wedding planner in North America managing 10–30 weddings a year, who pays a professional tier ($200–400/month) and acts as a distribution channel. The volume user is the engaged diaspora couple planning a multi-event wedding, at $30–60/month self-managing or $10–20 bundled with a planner. Parents get free read-only access as an adoption enabler.

The model is B2C for the MVP and B2B in Phase 2, sold as subscriptions. Contract review serves both primary personas — saving planners 30–45 minutes per contract and giving self-managing couples confidence on the most intimidating step.

Why it matters

Indian diaspora weddings are exceptionally high-spend — 6–8x the average US wedding — and AI adoption among couples nearly doubled year over year to 36% in 2025. The global Indian wedding market represents $15B+ annually, and US wedding planning services are projected to grow at an 8.5% CAGR through 2030. No competitor properly serves Indian multi-event coordination in North America, and the one culturally intelligent player (BollyWeds) is agency-only.

A startup targeting a V1 launch (July 2026), Shaadi AI's contract suite is the strongest wedge: the clearest market gap, the most demonstrable AI flow in a prototype, the strongest monetization hook, and the trust-building entry point to the rest of the platform.

At a glance

Project
Shadi AI
Built by
Varun Maryada
One-liner
Shadi AI is an AI-powered wedding planning platform designed for the Indian diaspora in North America.
View the project page